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Threading support rework.

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Placed parallel pragmas as macros; implemented deterministic thread reduction in style of
BFM.
This commit is contained in:
Peter Boyle
2015-05-12 07:51:41 +01:00
parent b1d2c60d07
commit 6103c29ee3
26 changed files with 276 additions and 184 deletions
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111
lib/lattice/Grid_lattice_reduction.h
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@ -7,69 +7,85 @@ namespace Grid {
#endif
////////////////////////////////////////////////////////////////////////////////////////////////////
// Reduction operations
// Deterministic Reduction operations
////////////////////////////////////////////////////////////////////////////////////////////////////
template<class vobj>
inline RealD norm2(const Lattice<vobj> &arg){
typedef typename vobj::scalar_type scalar;
typedef typename vobj::vector_type vector;
decltype(innerProduct(arg._odata[0],arg._odata[0])) vnrm;
scalar nrm;
//FIXME make this loop parallelisable
vnrm=zero;
for(int ss=0;ss<arg._grid->oSites(); ss++){
vnrm = vnrm + innerProduct(arg._odata[ss],arg._odata[ss]);
}
vector vvnrm =TensorRemove(vnrm) ;
nrm = Reduce(vvnrm);
arg._grid->GlobalSum(nrm);
return real(nrm);
}
template<class vobj> inline RealD norm2(const Lattice<vobj> &arg){
ComplexD nrm = innerProduct(arg,arg);
return real(nrm);
}
template<class vobj>
inline ComplexD innerProduct(const Lattice<vobj> &left,const Lattice<vobj> &right)
// inline auto innerProduct(const Lattice<vobj> &left,const Lattice<vobj> &right)
//->decltype(innerProduct(left._odata[0],right._odata[0]))
{
typedef typename vobj::scalar_type scalar;
decltype(innerProduct(left._odata[0],right._odata[0])) vnrm;
typedef typename vobj::scalar_type scalar_type;
typedef typename vobj::vector_type vector_type;
vector_type vnrm;
scalar_type nrm;
scalar nrm;
//FIXME make this loop parallelisable
vnrm=zero;
for(int ss=0;ss<left._grid->oSites(); ss++){
vnrm = vnrm + innerProduct(left._odata[ss],right._odata[ss]);
GridBase *grid = left._grid;
std::vector<vector_type,alignedAllocator<vector_type> > sumarray(grid->SumArraySize());
for(int i=0;i<grid->SumArraySize();i++){
sumarray[i]=zero;
}
nrm = Reduce(vnrm);
PARALLEL_FOR_LOOP
for(int thr=0;thr<grid->SumArraySize();thr++){
int nwork, mywork, myoff;
GridThread::GetWork(left._grid->oSites(),thr,mywork,myoff);
decltype(innerProduct(left._odata[0],right._odata[0])) vnrm=zero; // private to thread; sub summation
for(int ss=myoff;ss<mywork+myoff; ss++){
vnrm = vnrm + innerProduct(left._odata[ss],right._odata[ss]);
}
sumarray[thr]=TensorRemove(vnrm) ;
}
vector_type vvnrm; vvnrm=zero; // sum across threads
for(int i=0;i<grid->SumArraySize();i++){
vvnrm = vvnrm+sumarray[i];
}
nrm = Reduce(vvnrm);// sum across simd
right._grid->GlobalSum(nrm);
return nrm;
}
template<class vobj>
inline typename vobj::scalar_object sum(const Lattice<vobj> &arg){
inline typename vobj::scalar_object sum(const Lattice<vobj> &arg){
GridBase *grid=arg._grid;
int Nsimd = grid->Nsimd();
typedef typename vobj::scalar_object sobj;
typedef typename vobj::scalar_type scalar_type;
vobj vsum;
sobj ssum;
vsum=zero;
ssum=zero;
//FIXME make this loop parallelisable
for(int ss=0;ss<arg._grid->oSites(); ss++){
vsum = vsum + arg._odata[ss];
std::vector<vobj,alignedAllocator<vobj> > sumarray(grid->SumArraySize());
for(int i=0;i<grid->SumArraySize();i++){
sumarray[i]=zero;
}
PARALLEL_FOR_LOOP
for(int thr=0;thr<grid->SumArraySize();thr++){
int nwork, mywork, myoff;
GridThread::GetWork(grid->oSites(),thr,mywork,myoff);
vobj vvsum=zero;
for(int ss=myoff;ss<mywork+myoff; ss++){
vvsum = vvsum + arg._odata[ss];
}
sumarray[thr]=vvsum;
}
vobj vsum=zero; // sum across threads
for(int i=0;i<grid->SumArraySize();i++){
vsum = vsum+sumarray[i];
}
typedef typename vobj::scalar_object sobj;
sobj ssum=zero;
std::vector<sobj> buf(Nsimd);
extract(vsum,buf);
for(int i=0;i<Nsimd;i++) ssum = ssum + buf[i];
arg._grid->GlobalSum(ssum);
return ssum;
@ -77,13 +93,15 @@ namespace Grid {
template<class vobj> inline void sliceSum(const Lattice<vobj> &Data,std::vector<typename vobj::scalar_object> &result,int orthogdim)
{
typedef typename vobj::scalar_object sobj;
GridBase *grid = Data._grid;
assert(grid!=NULL);
// FIXME
std::cout<<"WARNING ! SliceSum is unthreaded "<<grid->SumArraySize()<<" threads "<<std::endl;
const int Nd = grid->_ndimension;
const int Nsimd = grid->Nsimd();
@ -94,10 +112,8 @@ template<class vobj> inline void sliceSum(const Lattice<vobj> &Data,std::vector<
int ld=grid->_ldimensions[orthogdim];
int rd=grid->_rdimensions[orthogdim];
sobj szero; szero=zero;
std::vector<vobj,alignedAllocator<vobj> > lvSum(rd); // will locally sum vectors first
std::vector<sobj> lsSum(ld,szero); // sum across these down to scalars
std::vector<sobj> lsSum(ld,zero); // sum across these down to scalars
std::vector<sobj> extracted(Nsimd); // splitting the SIMD
result.resize(fd); // And then global sum to return the same vector to every node for IO to file
@ -108,6 +124,7 @@ template<class vobj> inline void sliceSum(const Lattice<vobj> &Data,std::vector<
std::vector<int> coor(Nd);
// sum over reduced dimension planes, breaking out orthog dir
for(int ss=0;ss<grid->oSites();ss++){
GridBase::CoorFromIndex(coor,ss,grid->_rdimensions);
int r = coor[orthogdim];